diff_of_means ratio_of_sd amplitude_ratio_of_means maximum_error ks_mean_on_coarse_res_with_extremes amount_rainy_hours_ratio_of_means qqplot_mae acf_mae extremogram_mae
lstm.cesm2.ssp245 0.11% 0.986 0.932 0.348 0.132 0 0.333 0.035 0.021
lstm.cesm2.ssp370 0.12% 0.982 0.929 0.368 0.069 0 0.353 0.033 0.009
nv.mri_esm2_0.ssp370 -0.13% 1.109 0.961 0.114 0.287 0 0.631 0.068 0.034
lstm.mri_esm2_0.ssp434 0.15% 0.988 0.922 0.381 0.203 0 0.431 0.043 0.012
lstm.ec_earth3.ssp434 0.15% 0.999 0.947 0.378 0.146 0 0.425 0.048 0.021
lstm.mri_esm2_0.ssp245 0.16% 0.978 0.917 0.383 0.195 0 0.504 0.043 0.029
xgboost.mri_esm2_0.ssp370 -0.16% 1.050 0.842 0.380 0.308 0 0.519 0.106 0.028
nv.mri_esm2_0.ssp434 -0.17% 1.155 0.963 0.108 0.276 0 0.878 0.085 0.053
lstm.mri_esm2_0.ssp370 0.18% 0.978 0.925 0.365 0.230 0 0.538 0.032 0.016
xgboost.mri_esm2_0.ssp434 -0.19% 1.088 0.855 0.381 0.311 0 0.689 0.115 0.025
lstm.cesm2.ssp585 0.19% 0.979 0.928 0.357 0.056 0 0.552 0.033 0.011
cnn.cesm2.ssp245 0.20% 1.001 0.935 0.120 0.161 0 0.590 0.059 0.039
cnn.cesm2.ssp370 0.21% 0.995 0.928 0.122 0.058 0 0.609 0.058 0.016
cnn.ec_earth3.ssp434 0.23% 1.016 0.983 0.138 0.122 0 0.677 0.056 0.022
cnn.mri_esm2_0.ssp434 0.24% 0.999 0.925 0.128 0.230 0 0.688 0.063 0.023
cnn.mri_esm2_0.ssp245 0.25% 0.987 0.922 0.136 0.189 0 0.737 0.062 0.039
cnn.mri_esm2_0.ssp370 0.26% 0.989 0.935 0.131 0.243 0 0.766 0.050 0.025
nv.ec_earth3.ssp434 -0.27% 1.019 0.946 0.163 0.176 0 0.775 0.065 0.021
cnn.cesm2.ssp585 0.28% 0.995 0.927 0.124 0.062 0 0.818 0.059 0.019
xgboost.ec_earth3.ssp434 -0.28% 0.960 0.726 0.342 0.265 0 0.842 0.136 0.031
nv.mri_esm2_0.ssp245 -0.32% 1.153 0.962 0.112 0.304 0 1.031 0.086 0.100
xgboost.mri_esm2_0.ssp245 -0.33% 1.081 0.873 0.381 0.303 0 0.962 0.108 0.025
nv.cesm2.ssp585 -0.44% 0.995 0.958 0.111 0.053 0 1.294 0.031 0.016
xgboost.cesm2.ssp585 -0.47% 0.940 0.808 0.365 0.071 0 1.381 0.082 0.018
nv.cesm2.ssp245 -0.51% 0.997 0.956 0.126 0.137 0 1.482 0.034 0.041
xgboost.cesm2.ssp245 -0.52% 0.939 0.813 0.375 0.147 0 1.534 0.081 0.025
nv.cesm2.ssp370 -0.57% 0.967 0.959 0.127 0.041 0 1.651 0.019 0.017
xgboost.cesm2.ssp370 -0.59% 0.911 0.805 0.363 0.081 0 1.734 0.072 0.024

Time series of the first days

How Often Peaks Hit Hourly

QQ Plot

Distribution of the undownscaled value on days with estimated extremes values.

On the x-axis we have the daily mean (standardized). It says Undownscaled value, but is the daily mean after the downscaling. A good idea is to plot the original undownscaled value.

The purpose of this plot is to illustrate the distribution of P(undownscaled value | we predicted an extreme). This is useful because it reveals how much information we can recover concerning extreme events. If the distribution is skewed to the right, it suggests that we’re predicting extreme values only when extreme values have already occurred. Conversely, if the lower tail of the distribution resembles the reanalysis data, it indicates that we can capture short-duration extremes (e.g., brief periods of heavy rainfall, such as an intense downpour lasting an hour before stopping).

Autocorrelogram

Extremogram